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Record W4388869897 · doi:10.2196/50973

Barriers and Facilitators Associated With Remote Monitoring Adherence Among Veterans With Pacemakers and Implantable Cardioverter-Defibrillators: Qualitative Cross-Sectional Study

2023· article· en· W4388869897 on OpenAlex
Sanket S. Dhruva, Merritt H. Raitt, Scott Munson, H. J. Moore, Pamela H. Steele, Lindsey Rosman, Mary A. Whooley

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Cardio · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteQuality Enhancement Research InitiativeNational Institutes of HealthU.S. Department of Veterans Affairs
KeywordsMedicineVeterans AffairsFamily medicineCross-sectional studyFocus groupHealth careInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: The Heart Rhythm Society strongly recommends remote monitoring (RM) of cardiovascular implantable electronic devices (CIEDs) because of the clinical outcome benefits to patients. However, many patients do not adhere to RM and, thus, do not achieve these benefits. There has been limited study of patient-level barriers and facilitators to RM adherence; understanding patient perspectives is essential to developing solutions to improve adherence. OBJECTIVE: We sought to identify barriers and facilitators associated with adherence to RM among veterans with CIEDs followed by the Veterans Health Administration. METHODS: We interviewed 40 veterans with CIEDs regarding their experiences with RM. Veterans were stratified into 3 groups based on their adherence to scheduled RM transmissions over the past 2 years: 6 fully adherent (≥95%), 25 partially adherent (≥65% but <95%), and 9 nonadherent (<65%). As the focus was to understand challenges with RM adherence, partially adherent and nonadherent veterans were preferentially weighted for selection. Veterans were mailed a letter stating they would be called to understand their experiences and perspectives of RM and possible barriers, and then contacted beginning 1 week after the letter was mailed. Interviews were structured (some questions allowing for open-ended responses to dive deeper into themes) and focused on 4 predetermined domains: knowledge of RM, satisfaction with RM, reasons for nonadherence, and preferences for health care engagement. RESULTS: Of the 44 veterans contacted, 40 (91%) agreed to participate. The mean veteran age was 75.3 (SD 7.6) years, and 98% (39/40) were men. Veterans had been implanted with their current CIED for an average of 4.4 (SD 2.8) years. A total of 58% (23/40) of veterans recalled a discussion of home monitoring, and 45% (18/40) reported a good understanding of RM; however, when asked to describe RM, their understanding was sometimes incomplete or not correct. Among the 31 fully or partially adherent veterans, nearly all were satisfied with RM. Approximately one-third recalled ever being told the results of a remote transmission. Among partially or nonadherent veterans, only one-fourth reported being contacted by a Department of Veterans Affairs health care professional regarding not having sent a remote transmission; among those who had troubleshooted to ensure they could send remote transmissions, they often relied on the CIED manufacturer for help (this experience was nearly always positive). Most nonadherent veterans felt more comfortable engaging in RM if they received more information or education. Most veterans were interested in being notified of a successful remote transmission and learning the results of their remote transmissions. CONCLUSIONS: Veterans with CIEDs often had limited knowledge about RM and did not recall being contacted about nonadherence. When they were contacted and troubleshooted, the experience was positive. These findings provide opportunities to optimize strategies for educating and engaging patients in RM.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.358
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it